Reconstructed datasets: In our experiment, we adopt two Raw MR image datasets to train our proposed CLGNet and the other methods: (1) Calgary-Campinas-359 Brain Reconstructed data (CC-359 Brain) [1]} provides 45 fully-sampled T1-weighted Brain MR subjects acquired on a clinical MR scanner (Discovery MR750; General Electric (GE) Healthcare, Waukesha, WI) and the matrix size is \(256 \times 256\) . In addition, the CC-359 dataset includes the training dataset (25 subjects), the validation dataset (10 subjects), and the test dataset (10 subjects). (2) FastMRI [2]} is the largest open-access raw MR image dataset. In our work, we select the single-coil Knee data to train and test the proposed CLGNet and the other compared methods. The single-coil Knee data include 973 training subjects and 199 validation subjects, while the test subjects are not provided. Hence, we evaluate the performance of our proposed CLGNet and the other methods on the validation subjects.
